Banca de QUALIFICAÇÃO: LETICIA AINOAN NUNES DE SOUSA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : LETICIA AINOAN NUNES DE SOUSA
DATE: 09/07/2026
TIME: 09:00
LOCAL: Laboratório de Inovação Tecnológica em Saúde (LAIS)
TITLE:

Computational modeling of outcomes in HIV patients based on health regulation data

KEY WORDS:

HIV; Data Science; Artificial Intelligence; Data Integration; Machine Learning; Healthcare Regulation.

PAGES: 15
BIG AREA: Engenharias
AREA: Engenharia Biomédica
SUMMARY:

The increasing digitalization of healthcare systems has expanded the availability of data from clinical records, epidemiological surveillance systems, administrative databases, and healthcare regulation platforms. However, the integration and analysis of these data sources still represent significant challenges, particularly in contexts characterized by data heterogeneity and the complexity of health-related phenomena. In the context of HIV, these limitations hinder a comprehensive understanding of the multiple clinical, epidemiological, socioeconomic, and healthcare-related factors that influence patient outcomes throughout their care trajectories.

In this scenario, this research proposes a Data Science and Artificial Intelligence-based approach for the integration and analysis of heterogeneous data related to people living with HIV. The proposed framework encompasses the triangulation of information from different health information systems, including clinical, epidemiological, socioeconomic, and healthcare regulation data, with the aim of investigating factors associated with clinical outcomes and healthcare trajectories.

To achieve this goal, machine learning methods, longitudinal analysis, and explainable artificial intelligence techniques will be employed to identify patterns, risk factors, and barriers to healthcare access. As a scientific contribution, this study is expected to develop computational models capable of improving the understanding of HIV-related determinants and providing support for intelligent decision-making systems, contributing to evidence-based healthcare planning, monitoring, and management.

COMMITTEE MEMBERS:
Interno - 1153006 - LUIZ AFFONSO HENDERSON GUEDES DE OLIVEIRA
Interno - 2488270 - RICARDO ALEXSANDRO DE MEDEIROS VALENTIM
Externo ao Programa - 1510735 - DANILO ALVES PINTO NAGEM - UFRNExterna ao Programa - 2562782 - KARILANY DANTAS COUTINHO - UFRNExterna à Instituição - JANAÍNA LUANA RODRIGUES DA SILVA VALENTIM - UC
Externo à Instituição - JOÃO PAULO QUEIROZ DOS SANTOS - IFRN